Analysis method and apparatus utilizing color algebra and image processing techniques

ABSTRACT

A method and apparatus for analyzing an illuminated subject. In the preferred embodiment, the subject is a stained blood cell. A first signal is produced which represents a first predetermined wavelength band of the subject modified illumination at a region in the subject. A second signal is produced which represents a second predetermined wavelength band of the subject modified illumination at the region. The two wavelength bands are selected to produce differential contrast between at least two different regions in the subject. The two signals are algebraically combined with thresholding to classify the subject region in at least one of a predetermined number of categories. Further, signal processing is employed to compile partial and complete features for each region or cell.

[ Nov. 26, 1974 ANALYSIS METHOD AND APPARATUS 3,699,336 10/1972 Ehrlichet a1. 356/39 x UTILIZING COLOR AL EB AND IMAGE 3,705,771 12/1972Friedman et a1 356/39 3,714,372 l/l973 Rosen et a1. 235/92 PC XPROCESSING TECHNIQUES 3,715,601 2/1973 Tucker et a]. 356/39 X [76]Inventor: James E. Green, 56 Coffey St., 3,740,143 6/1973 Groner et a1.356/39 Boston, Mass. 02122 3,770,349 11/1973 Legoretta-Sanchez 356/39 X[22] Sept 1972 Primary Examiner-Joseph F. Ruggiero [2]] Appl. No.:286,043 Attorney, Agent, or Firm-Richard J. Birch, Esq.

52 us. ca 235/1513, 128/2 0, 356/39 [57] ABSTRACT [51] lint. C1. G0ln33/16 A method and apparatus for analyzing an illuminated [58] Field ofSearch 235/1513, 151.35, 92 PC; subject. In the preferred embodiment,the subject is a 444/1; 324/71 CP; 178/68; 128/2 G, 2 L, stained bloodcell. A first signal is produced which DIG. 5; 356/39, 42, 201-206represents a first predetermined wavelength band of the subject modifiedillumination at a region in the References Cited subject. A secondsignal is produced which represents UNITED STATES PATENTS a secondpredetermined wavelength band of the sub- 3,214,574 10/1965 Landsman etal. 340/1463 x modified illumination at the region- The two 3.315.2294/1967 Smithline 340/1463 X wavelength bands are selected to producedifferential 3,327,117 6/1967 Kamemsky H 356/36 X contrast between atleast two different regions in the 3,327,119 6/1967 Kamentsky.... 356/51x Subject. The two signals are algebraically combined 3,408,485 10/1968Scott et al 340/1463 X with thresholding to classify the subject regionin at 3,413,464 11/1968 Kamentsky 356/36 X least one of a predeterminednumber of categories. 2.2 29934 12/1970 Rothermel et a1. 235/92 PC XFurther, signal processing is employed to compile 6* lg/lgn wheeless' eta] 356/39 X tial and complete features for each region or cell. /l972Kamentsky et al. 356/39 X 3,684,377 8/1972 Adams et al 356/36 59 Claims,12 Drawing Figures Blood Sample Preparation & Dom Staining ControlSignals l l Figure 4 Flgure 5 Figure 6,7 Figure 9 Figure 3 Histogram 8rClassify Image Assign Cell Figure 8 Store Cell Magnify, Scan, 81 --1Threshold Points, Derive 1 Number or -0 Compile Cell Features lnDigitize image image Points Feature Compilation "Tag" Features MainMemory Control Signals Histogram Analysis Computer CPU Focus ControlControl Data Memory Output PATENTL llZlV 2 6 IBM 3.851.156 SHEET 2 0F 9Magnify Bl Scan Dlgilize Threshold Spatial Filler Color Logic Delay,

Background Subtract DATA A Verlical Connection Control Signals:

Feature Storage Size, Color, Denslly,

Conlrol Signals:

Penmeler "W le Partial Fealures for Cell Segment Assign Cell "Tug" ofNumber lo Cell Segment pile Compleie Fealures from Parliol Fealuresunder Cell "T Cla SSify Cell PATENIEQLSVZBISM 3.851 ,156

SHEU 1. OF 9 FIGU 30 G AID E B AID *0 IHuminoTion H Source sum 8 or 9 mm w c we m w M M m u D 2/, 2/ a W m I l- .m R S A C r C m B z R H a a Za 1 my 2 m I b j. J m m A w w 2 2 2 2 L & rs & r n n 8 m 6 WW M m m 8 "MD l .ll: r 2m 8 A B C m U 0 y Z Z Z P g N C 8 is wl|i||l||1|l1||i|i c mm b w H w 08 s 8 l 2 2 n o S S r. w D e D a I u I D l I c .l... A C .l.m s. B a Z TL Z P h A m N N M 9 NW N C A A mom M M no G C C D D D ID 3 2w. m OH RH. Mun A u 8 2 MM/ 2/ m mm m yt N z u 3 m 2 2 r Q IUD: u N+|| AH m M W R D D D SPR PRR

DPWCE) ANALYSIS METHOD AND APPARATUS UTILIZING COLOR ALGEBRA AND IMAGEPROCESSING TECHNIQUES BACKGROUND OF THE INVENTION The present inventionrelates to subject analysis methods and systems in general and, moreparticularly, to a method and. apparatus for particle analysis whichutilizes color algebra and image processing techniques.

The need for an accurate, fast and relatively inexpensive system foranalyzing particulate matter entrained in a gas or liquid exists in manyfields of current technology. For example, recent activities in the areof pollution analysis and control have emphasized the need for a meansfor particle identification, classification and morphology analysis. Asimilar need also exists in the field of medical technology forautomating labor intensive medical laboratory procedures, such as bloodanalysis.

The recent spiraling rise of medical care cost have raised the hope thatthese costs could be reduced by the application of automation technologyto the labor.

mated blood analysis. Technions SMA system for plasmaanalysis andI-Iemalog System for cell analysis, and Coulter Electronics ModelS cellcounter are well known examples. Using different technologies, theHemalog and Coulter S generally provide a costcompetitive count of thevarious particle constituents present in a blood sample. Thebasicconcept, common to both techniques, involves flowing athin column ofdiluted blood past a sensor which detects whether a solid particle ispresent in the liquid medium. This concept, commonly calledflow-through, provides a count of the particles present, but does notprovide any qualitative information regarding the identity of theseparticles or of their morphology.

Therefore, it is necessary to pre-segregate the sample to determinewhether the instrument is counting a RBC or a WBC. These two types ofcells have significantly different chemical properties, so they can beseparated relatively easily. However, it is not possible to furtherautomatically differentiate these cells according to their individualmorphological differences using currently available commercialtechnology.

Nevertheless, such a differentiation is extremely important in aboutpercent of all hospital patients, and it is highly desirable in 50percent of the patients. This is particularly true of the numerous typesof WBCs whose relative concentration and individual morphology areextremely important. Of lesser importance, but

still significant isthe detection of abnormal red cell morphology..Thesemeasurements, commonly known as the Differential count, are currentlyperformed by manual labor.

There are two basic approaches to differentiating a single cell bymorphology; a direct or pattern recognition approach and, an indirectapproach. The latter relies on there being indirect signatures ofchemical differences which have a high degree of correlation with thedirect signature of morphological differences in the basic WBCs types.Technions Hemalog-D, the only commercially announced differentialmeasurement sys tem, employs this approach, using enzymatic stains asthe chemical signature to separate five basic WBC types.

As in all indirect techniques, there are both theoretical and practicalsources of error. For example, abnormal variations within any of thefive basic WBC groups cannot be detected. In a high risk hospitalpopulation, 10 percent to 20 percent of the patients may have relativelynormal distribution among; the five chemical groups, but still havemorphological abnormalities indicative of a pathology. In other words,the morphological/chemical correlation is incomplete, resulting in falsenegatives, the most serious type of error. Furthermore, a percentage ofany healthy population will have unusually low enzyme levels with noaccompanying morphological abnormalities or clinical symptoms thusresulting in uneconomical false positives. In addition, the importantRBC morphology is not provided by the indirect technique.

In the direct approach, the morphology of the particles or cells isexamined directly using computer pattern recognition techniques,Performing the blood cell differential measurement using patternrecognition techniques is within the current state of the scientificart. To date, the problem has been economic; specifi cally, theinstruments which employed current technology required high capacitycomputer equipment which was too costly for this particular commercialapplication. The same general problems exist in otherfields oftechnology employing particle analysis techniques.

It is, accordingly, a general object of the invention to provide animproved system for subject analysis.

It is a specific object of the invention to provide a particle analysissystem which utilizes color algebra and, in the preferred embodiment,employs color algebra in conjunction with imageprocessing techniques.

It is another specific object of the present invention to provide, asone embodiment thereof, a commercially feasible automated blooddifferential measurement system.

It is still another specific object of the present invention to providean automated blood differential measurement system which utilizes pattemrecognition techniques in conjunction with chemical/optical signaturesto achieve a commercially feasible system.

It is a further object of the present invention to cmploy color algebratechniques which permit the use of simplified algorithms.

It is still a further object of the present invention to provide anautomated blooddifferential system which employs scanning and dataprocessing components which, in conjunction, with color algebratechniques, drastically reduce both the computer capacity requirementand the processing time.

It is a feature of the present invention that the automated blooddifferential measurement system embodiment provides increased accuracyover existing systems due to the inherent superiority of a directmeasurement technique over an indirect measurement technique togetherwith the additional ability to make finer distinctions between WBCs inany one of the live basic types, the ability to recognize abnormal v.normal morphology; and the ability to provide RBC measurements.

It is still another feature of the blood analysis embodiment of thepresent invention that conventional blood staining procedures can beemployed with the color algebra technique of the invention.

These objects and other objects and features of the present inventionwill best be understood from a detailed description of a preferredembodiment thereof, selected for purposes of illustration, and shown inthe accompanying drawings, in which:

FIG. 1A is a functional block diagram of the blood analysis embodimentof the invention;

FIG. 1B is a more detailed functional block diagram of the inventionshowing data flow;

FIGS. 2A through 2C are representative histograms of a blood sample;and,

FIGS. 3 through 9 depict a partial block and diagrammatic form the bloodanalysis embodiment of the invention.

The particulate matter analysis system of the present invention can beused for analyzing many different types of particular matter. However,for purposes of illustration and ease of description, the followingdiscussion will be directed to the blood analysis embodiment of theparticulate matter analysis system as shown in functional block diagramform in FIG. 1.

The present invention utilizes color algebra techniques to reduce boththe computer capacity requirement and the processing time. Beforeproceeding with the detailed description of the present invention, itwill be helpful to briefly review some basic information with respect tocolor.

The perception of color is a complex physiological phenomenon whichoccurs in response to variations of the spectral components of visiblelight impinging upon the retina. The quantitative description of coloris complicated by the fact that the same perceived color can be producedby numerous combinations of different spectral components.

In order to standardize the description of colors in scientific work, asystem of chromaticity measurements was developed by the CH2. (CommisionInternationale de l Eclairage) in 1931. The chromaticity measurementsare obtained by convolving the spectral components of the illuminationwith three specific spectral distributions to produce Red, Green, Blueintensities. The percent fraction of each of these intensities isexpressed as X, Y, and Z coordinates, respectively, where:

Y G/(R G B) The three spectral distributions have been established sothat any combination of wavelengths which produces the same subjectivecolor will also produce the same chromaticity coordinates.

The three components X, Y, and Z, generally corresponding to thefraction of Red, Green and Blue light in the illumination, can beplotted on a two dimensional graph. Chromaticity coordinates have beenused in the past as one or more features in multi-dimensional featurespace pattern recognition systems to recognize and classify, among otherthings, blood cells.

Biological specimens are stained to improve contrast of the normallytransparent tissues, and render various structures more recognizable.Blood cells are normally stained with a Romanovsky type stain, e.g.,Wrights stain, a two component stain system comprising a red and bluedye. The blue stain component stains cell nuclei, the cytoplasm oflymphocytes, and certain granules in the cytoplasm of some of the othercells, in particular the basophilic granules of the basophils. The redstain component is absorbed by the red cells, lightly by. the cytoplasmof most white cells, by eosinophil granules and to some extent cellnuclei. These staining patterns are not absolute or mutually exclusivebecause almost every cell part absorbs both stain components to someextent. However, usually one or the other stain component is predominentand this predominance forms the basis of a functional analysis systemutilizing the color differences. Thus, the cytoplasm of most cells, withthe exception of lymphocytes, is stained light violet to red-orange, thecytoplasm of lymphocytes is stained a pale blue, the nucleus of thecells is stained a deep purple, the eosinophil granules are stained adeep red to orange, and the basophil granules are stained deeply blue.

For blood cells that have been stained with Wrights stain, the redabsorption peak of methylene blue and its derivatives occurs at about570-600 n.m., the blueabsorption peak of the Eosin-Y stain componentoccurs at about 500-530 n.m. and finally, the blueviolet naturalabsorption peak of hemoglobin occurs at about 400-420 n.m.

The present invention utilizes this color information to generateinformation with respect to the differential contrast between and/oramong various points or regions in the cell. The color information isreduced to differential-contrast information by illuminating the samplewith white light with subsequent filtration by narrow wavelength bandfilters. Alternatively, the differential-contrast information can beproduced by illuminating the blood sample with selected narrowwavelength bands of light.

Each point or region in the cell will modify the light in accordancewith its absorption, transmission and reflectivity characteristics. Theterm contrast refers to a substantial difference in the modification ofthe light by two or more cell points or regions at one wavelength band.The term differential contrast refers to a dissimilar pattern ofcontrasts at two or more wavelength bands.

The appropriate wavelength bands are selected with respect to thespectral content of the stain or dye systemss light modifyingcharacteristics and/or with respect to the light modifyingcharacteristics of the natural material, e.g. hemoglobin. Withappropriately selected wavelength bands, the desired differentialcontrast of the various cell points or regions to be recognized isestablished by their'marked density and/or reflectivity differences.Thus, when the wavelength bands are properly chosen, a particular cellregion, such as WBC cytoplasm will be very dense at one wavelength bandand relatively transparent at another. Another region such as, RBCcytoplasm will display a different contrast pattern at the samewavelength bands. The differential contrast of the cell componentsestablished by the choice of the various wavelength bands permits theidentification and classification of cell components or regions by meansof a color algebra illustrated be low.

The color algebra can be implemented by sampling and digitizing thesignal representing the sample moditied illumination at each of thewavelength bands to produce a digitized serial data stream, and thenhistogramming the digitized values as shown in FIG. 2.Characteristically, the histograms of the points in the scanned bloodsample exhibit two or more groups of points, or peaks at differentdensity levels. For exam ple, as shown in FIG. 2, the peaks maycorrespond to a group of background points at about the same density, orto another group of somewhat denser cell cytoplasm points or possibly to'a third group of very dense cell nucleus points. Several types ofcellular components may be combined into a peak at one wavelength, butwill be separated at another wavelength. For example, in FIG. 2, WBC andRBC nuclei, basophil granules and lymphocytecytoplasm are combined inpeak 3 of histogram A, but are separated into peaks 5, 6 and 7 ofhistogram B.

In practice,histogramming has proved to be a feasi ble method forestablishing thresholds. However, it should be understood that the coloralgebra also can be implemented by arbitrarily establishing thethresholds without sampling, digitizing or histogramming. For example,asuitable color algebra can be used to detect sample regions of bloodcells flowing in a liquid stream past a sensor. In this situation, noscanning, sampling, digitizing or histogramming is employed.

Thresholds are established to Separate the peaks of the histograms. Thethresholds are shown as T,,, T and T with T B illustrating the use ofmultiple'thresholds. Any point in the digitized data stream can then becharacterized as a thresholded signal in binary form as exceeding or notexceedingthe various thresholds.

The thresholded signals can be combined to produce the following coloralgebra:

Background RBC Cytoplasm RBC Neucleus WBC Neucleus Monocyte BasophilGranules Lymphocyte Cytoplasm This color algebra is applicable for thepreviously discussed example of a Wrights stained blood sample and thewavelength bands set forth above. Other color algebra can be employed toclassify cell components stained with other dye systems or using thecharacteristic absorption of other natural cellular constituents, thewavelength bands again being selected to provide differential contrastbetween at least two different regions in the sample.

It can be seen from the table that the color algebra characterizes aparticular point or region as being in one of a number of cell componentclassifications. In addition, the color algebra also permitsdifferentiation between cell components and background area in the bloodsample. Thus, the thresholded signals can be algebraically combined toproduce sample region classification signals.

The preceding example of a color algebra illustrates the classificationof the cell components and background by algebraic combination ofthresholded sig- 7 nals. Alternatively, the signalscan be algebraicallyordinate calculationsand subsequent complicated pattern recognition dataprocessing. It also will be appreciated that it is not necessary tostain the cells to use the differential contrast and color algebrafeatures of the present invention. Alternatively, native constituents ofthe cells may be utilized to provide the necessary contrast patterns.For instance, in addition to the natural absorption of hemoglobin near400 n.m., the absorption peak of DNA (normally found in cell nuclei) at258 um. and the absorption peak of proteins (normally foundpredominently in the cell cytoplasm) at 280 n.m. can be used as thewavelength bands. Because of the partial overlap of absorption waves ofthese two cellular constituents and the presence of some otherconstituents which also absorb at these wavelengths, the resulting coloralgebra is somewhat. more complicated than that employed with Wrightsstain. Furthermore, in using these three wavelength bands, the longexperience of the medical community with Wrights blood stain would belost. For this reason, the Wrights stain system is the one of choice.

It will further be appreciated that the color algebra feature of thepresent invention is not limited to three wavelength bands of thepreferred embodiment. Any two or more wavelength bands which willproduce differential contrast between at least two regions in thesubject of interest can be utilized to produce an appropriate coloralgebra.

Having described the differential contrast and color algebra concepts asthey relate to the present invention, I will now proceed with adescription of the general systems concept of the preferred embodiment.

Returning now to FIGS. 1A and 18, there is shown in block form thegeneral systems concept, the principles of operation and the data flowof the blood analysis embodiment.

In FIG. 1A, the blood sample is prepared for analysis by being spread ina thin layer on a glass slide or other suitable surface and stained witha suitable blood stain. Normally, the prepared slide is magnified by anoptical system (microscope) and a portion of themagnified image isscanned and digitized at several wavelength bands. Details of thisprocess will be presented in FIG. 3.The magnified image is then embodiedin two or morestreams of numbers (the digitized serial data signals)which represent the transmission or density of the image over the rasterof points.

There are three basic stages in the process of analysis of the scannedand digitized image: (I) the cells are located or localized; (2)quantitative features which characterize the cells in some desirable wayare extracted from the localized cell images; and, (3) using thesefeatures the cells are classified as normal, abnormal, neutrophil,lymphocyte, etc.

The previous state of the art method for performing these tasks was tostore the stream of numbers representing the image density at variouspoints in a computer memory. Then, algorithms stored in the computerwould localize the cells, extract the features and classify the cells.As an image contains a large number of points, a large memory wasrequired to store it. Also, since all three stages of the analysis wereperformed by the computer processor, it was of necessity fast andpowerful. Both of these factors required the use of a computer so costlythat to actually analyze blood smears in this way would be prohibitivelyexpensive.

The preferred embodiment does not use storage of any of the stream ofdigitized image points in a computer memory. It makes use of acombination of color algebra and simple preprocessing circuitry toreduce computer memory requirements to that just sufficient to storeonly the compiled features of the cells in the image. At the same time,the work the computer must perform is reduced to classification of thecells using the compiled features. Both of these characteristics permitthe use of a relatively simple and inexpensive computer. Even so, byrelieving the computer of the tedious localizing and feature extractiontasks, the present embodiment is able to operate much faster with asmall inexpensive computer than a previous state of the art design whichused a large expensive computer.

This combination of color algebra and preprocessing of the stream ofsampled and digitized points is further illustrated in the block diagramin FIGS. 1A and 1B. The points of each color representation of thedigitized image (the Digitized Serial Data Signals) are histogrammed andthresholded to produce Thresholded Signals. The background density issubtracted from the image density to produce a Data signal. Using coloralgebra, each image point is then classified as either background,neucleus, WBC cytoplasm or RBC to produce Sample Region ClassificationSignals. In the preferred embodiment, a line delay is employed toreestablish the vertical connection of two adjacent image lines. TheSample Region Classification Signals are then used to derive ControlSignals for identifying all segments on each scan line and for compilingthe cell features for each cell segment on a line-by-line basis. Detailsof these Control Signals will be discussed and elaborated in FIG. 5.

To keep the features for each encountered cell separate, each cell inthe field if given a cell number or tag. Circuitry to assign these tags,and correct errors which might occur, are discussed and elaborated uponin FIGS. 6 and 7.

The actual compilation of the partial features for each cell segment ona line-by-line basis is performed by the special circuitry shown inFIGS. 8 and 9. Using the FIG. 5 Control Signals, this circuitry operateson -to further classify the cells, usually by multidimensional featurespace analysis familiar to the art, to produce the differential countdata output. The instructions which perform this further classificationand perform overall system monitoring are shown residing in a separatecontrol memory. System monitoring functions include monitoring thehistograms and the compiled features to insure that the sample has beenproperly stained and that the system is performing within predeterminedoperating parameters, keeping track of the patients identification,monitoring the focus control, summarizing data over a large number ofcells, and averaging and outputting the summarized data.

It will be appreciated from the foregoing and following description thatthe preferred embodiment is one specific example of a more generalmethod and apparatus for subject analysis characterized by thecompilation of partial cell features from a scanned signal repre sentingthe sample. The preferred embodiment comprises a sophisticated analysissystem which isolates and analyzes each cell in scene containing manyblood cells. In order to accomplish this sophisticated analysis of acomplex scene, a number of types of control signals are generated fromboth normal and delayed sig nals, the partial cell features are compiledfrom identified cell segments in each scan line and then the completecell features are compiled from the partial features utilizing cell tagswhich have been assigned to each cell in the scene. However, a lesscomplex version of the invention can be employed to analyze a scenecontaining only one complete cell (or one cell of a particular type,such as a WBC). In this case, a single type of control signal is derivedfrom undelayed signals and are used to compile the partial and completecell features from the single cell without using cell tags.

Having described the overall systems concept and general operatingprinciples of the preferred embodiment, I will now discuss in detail thespecific circuitry of the embodiment.

Referring to FIG. 3, there is shown in diagrammatic and partial blockform an optical-to-electrical input stage for the blood cell analysissystem which is indicated generally by the reference numeral 10. Anopticalscanner 12 scans in raster fashion a field 14 which contains ablood cell sample 16. The sample 16 comprises a blood film composed ofred cells, white cells and platelets spread on a monolayer 18 on astandard glass slide 20.

The blood layer 18 is stained with a suitable stain which enhances themorphological components of the blood cells. A typical example of such astain is the previously mentioned Wrights stain. The stained blood layer18 is scanned within field 14 by means of the optical scanner 12. Forpurposes of illustration, the spacing between the scan lines shown inFIG. 3 has been greatly exaggerated and the relative movement of thefield 14 across the blood sample 16 has been indicated by relativemovement arrows 22. Furthermore, the optical system within scanner 12has been generalized in the drawings. It will be appreciated thatsuitable magnification stages and focusing control systems, e.g., amicroscope input to scanner 12 can be and normally would be, employed inthe blood analysis embodiment of the invention.

The blood sample 16 is illuminated by light from an illumination source11. the sample can be illuminated directly to provide reflectivemodification of the light The scanned output beam 24 from scanner 12 ispassed through a beam splitting prism 26 which divides the output beam24 into three separate beams 28a, 28b, and 280. Each beam 28 passesthrough the previously mentioned color filters 30a, 30b, and 300 andimpinges upon photo tubes 32a, 32b, and 320. Alternatively, dichroiccoatings can be used on the beam splitting prism 26 to achieve thedesired color separation. The electrical signal from the photo tube 32on output lines 34a, 34b, and 34crepresents in electrical form theoptical transmission of each segment of the scanned field 14. Theoptical transmission (linear) is converted to optical density(logaritmic) he means of log-converters 36a, 36b, and 36c. The analogoutput of the logconverters 36 is converted into a Digitized Serial DataSignal at a specified sampling interval by means of A/D converters 38a,38b, and 380. The outputs from A/D converters 38a, 38b, and 38c areidentified in FIG. I

as Digitized Serial Data Signals labeled A, B', and C.

Looking now to FIG. 4, the three channel data A, B and C is applied asan input to a histogrammer 40 and to corresponding signal levelcomparators 42a, 42b, and 420. During the first pass of scanner 12through field 14, the histogrammer 40 collects the histographicinformation within the field for each signal, i.e., the densitydistribution of the points within the field 14. The three histograms arethresholded and during the second scan of the field the thresholdedoutputs T T and T are applied to output lines 44a, 44b, and 440 as thesecond input to the corresponding comparators 42a, 42b and 42c. Themagnitude of the optical density data A, B, and C; is thus compared withthe preset thresholds T T and T to produce thresholdedsignals. Thepotential for thresholding a data signal more than once is illustratedin FIG. 2 by the label T and comparator 42c.

The output from each of the comparators 42a, 42b, and 42c is a ONE ifthe corresponding input is equal to or greater than the presetthreshold'T T or Tb (an over-threshold" signal) and ZERO if less thanthe threshold (an under-threshold signal). The thre- The timing of the 3X3 array and the line delays 50a and 52a is designed to provide a totaldelay of two scan lines through field 14 plus the time delay representedby shifting. the one bit data signal through three of the blocks in the3 X 3 array 48a. Thus, a one line delay for field 14 corresponds to thedelay produced by A A A and line delay 50a.

Given this delay configuration for the 3 X 3 array 48a and thecorresponding line delays 50a and 52a, it will be appreciated that the 3X 3 array 480 restores the vertical connection of points in threeadjacent lines within the scanned field by delaying two lines. Thesignals within the 3 X 3 array blocks A, through A, are applied tocorresponding input lines identified collectively by the referencenumeral 54a to a logic circuit shown in block form in FIG. 4 andidentified by the reference nu-, meral 56a. The logic circuit 56aperforms a spatial filtering function with respect to the center elementA in the 3 X 3 array. Normally, the output signal A from logic circuit56a is the same as the center element A in the 3 X 3 array 48a. However,if the center element A, is ZERO and all or most of the surroundingelements A, through A, and A through A are ONE, the logic circuit 56awill change the value of the output signal A to a ONE. Conversely, ifall or most of the elements surrounding a ONE center element are ZEROS,then the value of the center element A, is changed to ZERO for theoutput signal A from logic circuit 56a. The same sholded signal outputfrom each of the three channel comparators on output lines 46a, 46b, and46c is a onebit datum representing the presence or absence of anover-threshold signal.

For purposes of clarity in the drawings, relative shading has been usedon input and output lines to designate the type of signals thereon.Thus, looking at FIG. 4, a multiple number of bits is indicated by aheavy line,

such as, the output lines 44 from the histogrammer 40' while a one bitdata line is indicated by a relatively light line such as lines 46a,46b, and 460. A

The thresholded signals on comparator output line 46a is applied to a 3X 3 shift register array 48a. Selected outputs from the 3 X 3 array areinputted to line delays a and 52a. The line delays can be implemented ina variety of ways including delay lines, shift registers, etc. Theoutputs from the line delays 50a and 52a are fed back to the 3 X 3 shiftregister array 48. The separate sections within the 3 X 3 array areidentified by the letter A with suitable subscripts 1 through 9.

filtering is performed for the signals on input lines 46b and 46c.Forpurposes of clarity, the same reference numerals have been used inFIG. 4 with the corre- NUMBER OF SURROUNDING Os Valueof' 012 3 4- 5 6 8Element 5 0 111000000 I llllll000 The A, B, and C outputs from thecorresponding circuits 56a, 56b, and 560 are filtered versions of thedata in array blocks A B and C respectively.

The spatial filtering provided by the 3 X 3 array 48a, its correspondingline delays 50a and 52a and the logic circuit 56a is optional in thepresent invention. If a very clean signal with no noise is available,filtering is not necessary. However, since most practical electronicsystems are noisy, the preferred embodiment of the present inventionincludes the filtering circuit just described.

Referring now to FIG. 5, the thresholded and spatially filtered signalsA, B, and Cfrom the three logic circuits shown in FIG. 4 are applied asinputs to a color logiccircuit 58 shown in block form in FIG. 5. Thecolor logic circuit 58 processes the A, B, and C signals to producesample region classigication signals. In the preferred embodiment, thesesignals represent points in I the nuclei, white cell cytoplasm, and redcells in the 4) don't care The color logic circuit 58 produces threeoutput or sample region classification signals which indicate when apoint is part of a ceIls nucleus, white ceIIs cytoplasm or a red cell.These three outputs appear, respectively, on output lines 60, 62, and64, and are inputted to corresponding five block arrays 66, 68, and 70.Each array is provided with a line delay 72. The purpose of the linedelay is to delay the signal and thereby re-establish the verticalconnection of the points within the array. Note that a delay of a singleline was produced by the signal transition in the 3 X 3 array 48a shownin FIG. 4 as the signal progressed from block A to A The line delay 72shown in FIG. 5 then produces another single line of delay. It alsoshould be noted that the point A in the 3 X 3 array shown in FIG. 4 andthe point N shown in the five block array in F IG. 5 correspond to thesame point in the scanned field 14.

The output from the four array blocks N N N and N, are applied asinputs, on leads identified collectively by the reference numeral 74, toa nucleus perimeter control logic circuit 76.

The control logic circuit 76 is designed to produce control signals forthe system with respect to the perimeters of each detected nucleus. Thecontrol circuit 76 generates four control signals: straight perimeter,nu cleus (SPN); diagonal perimeter, nucleus (DPN), previous rowperimeter, nucleus (PRN); and, store previous row, nucleus (SPRN). Thetruth table for generating these four control signals is:

4 INPUT ELEMENTS OF LOGIC 76, 82, & 84 USING ARRAY 66 AS AN EXAMPLECONTENTS OF 4 ELEMENTS OF 5 BLOCK ARRAY Output of logic 76, 82, & 84:

' 0: 0, l, 2, 4, 8, 15, (6, excepting logic 76) STRAIGHT PERIMETER: 3,5, I0

DIAGONAL PERIMETER: 7, II, I3, I4, (6, 9, logic 76 only) ALTERNATEPERIMETER: I2

STORE ALTERNATE PERIMETER: 8, (9, excepting logic 76) Similar logic isalso applied with respect to the outputs from the white cell cytoplasmfive block array 68 and the red call five block array 70. The respectiveoutputs from these arrays are applied through input lines 78 and 80,respectively. to corresponding control logic circuits 82 and 84. Thewhite cell cytoplasm control logic circuit 82 generates four outputsignals: straignt perimeter, white cytoplasm (SPWC); diagonal perimeter,white cytoplasm (DPWC); previous row, white cytoplasm (PRWC); and, storeprevious row, white cytoplasm (SPRWC). Similarly, the red cell controllogic 84 also produces four outputs namely, straight perimeter, red cell(SPR); diagonal perimeter, red cell (DPR); previous row, red cell (PRR);and, store previous row, red cell (SPRR).

An additional control logic circuit 86 develops control signals basedupon input signals from the nucleus, white cytoplasm and red cell fiveblock arrays 66, 68 and 70, respectively. The input signals to logicarray 86 on input leads 88 comprise the signals from the N, and N blocksof the nucleus array 66; signals from the WC and WC, blocks of the whitecell cytoplasm array 68 and, finally signals from the R and R blocks ofthe red cell array 70. The control logic circuit 86 generates sevenoutput signals in accordance with the truth table as follows:

INPUT INTERMEDIATE CLASSIFICATIONS N WC R WBC Nucleus (WN) I O 0 WBCCytoplasm (WC) 0 I 0 RBC Nucleus (RN) I (I I RBC Cytoplasm (RC) 0 0 ITRANSITION OF INTERMEDIATE CLASSIFICATIONS IN ELEMENTS NO. 4 AND NO. 5IN ARRAYS NOS 66, 68, and 7() -Continued TRANSITION OF INTERMEDIATECLASSIFICATIONS IN ELEMENTS NO. 4 AND NO. 5 IN ARRAYS NOS. 66. 68 and 70Transition Count Store 4 5 N WC R W R LINK PINH RN WC 1 WC RN 1 l hibitsignal (PINH). The purpose of these two signals will be explainedsubsequently. The count nucleus signal (CNTN) and the count cytoplasmsignal (CNTC) are applied to an OR gate 90 which produces an outputsignal for indicating that white cell partial features are beingcompiled (CNTW).

It can be seen from FIG. 5 that the Perimeter Control Signals from logiccircuits 76, 82 and 84 are derived, inter alia, from signals which aredelayed by means of line delays 72. However, in a simpler embodiment ofthe invention, the line delays 72 can be omitted if the sample analysisdoes not require perimeter information and the concomitant use ofperimeter control signals. In such a simpler embodiment, there is also areduction in the complexity of the cell tagging logic which will bediscussed below in connection with FIGS. 6 and 7.

The control signals generated by the logic circuits shown in FIG. 5 areemployed to identify an encountered cell segment and to control thecompilation of the partial and complete features of the variouscomponents of the cells. The partial cell features, such as size,density, shape, perimeter, length, etc., are compiled on a line-by-Iinebasis for each identified cell segment. Each ell is assigned anappropriate number or tag in order to properly control the compilationof the complete features from the partial features for a particular cellsegment. The cell identification number or tag is passed from one row tothe next when there are vertically connected points in a cell.

The circuitry shown in FIGS. 6 and 7 is employed to generate and assignthe appropriate cell number or tag to the cell. From a functionalstandpoint, the circuitry must assign a new cell number to the cell ifthe cell has not been encountered previously in the scan of the field14. Conversely, the circuitry must assign the appropriate old cellnumber if the cell has been encountered previously. In some situations,the initial data mayindicate that a cell segment from a new cell hasbeen encountered when in fact the cell segment actually is part of apreviously encountered and identified cell. When this situation isrecognized, the new cell number must be removed from the cell segmentand the segment tagged with the appropriate old cell number.

The circuitry which accomplishes the cell identification or taggingfunction is shown in partial block and schematic form in FIG. 6 and inblock form in FIG. 7. Referring now to FIG. 6, there is shown a fiveblock tag array 92 and a line delay 94. The five blocks of the tag arrayare identified as T, through T These blocks correspond to the sameportion of thescanned image as A,A B,B and C C in FIG. 4; From afunctional standpoint, the purpose of the tag array 92 and itsassociated circuitry is to determine if there is any point in thescanned picture of the same cell type as point T which has previouslybeen assigned a cell number and which is touching point T If this is thecase, then the point in T should be assigned the same cell number.

The red and white blood cell numbers or tags are ob tained fromcorresponding UP-DOWN White and Red Blood cell counters 95 and 97,respectively. The operation of these counters will be described below.

Looking at FIGS. 5 and 6, the outputs from N WC, and R of the arrays 66,68, and 70, respectively, are applied as inputs to a logic circuit 96which is also identified in FIG. 6 by the designation S3. The logiccircuitry shown in S3 is duplicated in logic circuits 98,

100, and 102, which are designated respectively as S1, S2, and S4. Thesefour logic circuits SIS4 determine whether each of the pointsrepresented by T through T are of the same cell type as the pointrepresented by T The inputs to the logic circuits Sl-S4 correspond tothe same numbered blocks in the nucleus, white cell cytoplasm and redcell arrays 66, 68, and 70, respectively, shown in FIG. 5. Thus. for theS3 logic circuit the inputs comprise the signals from the N WC;, and Rblocks of the corresponding arrays and the count red (CNTR) and countwhite (CNTW) signals. For purposes of clarity, the count red and countwhite signals input lines have been omitted from S1, S2 and S4.

In each of the logic circuits S1S4, and as shown in detail in S3, thenucleus and white: cell cytoplasm signals are ORed by OR gate 104 toproduce a white cell output. The output of OR gate 104' is ANDed withthe signal count white (CNTW, FIG. 5) in AND gate 106 to indicate that Tand T are both white cell points. The R and count red cell signal (CNTR,FIG. 5) are also ANDed by an AND gate 108 to indicate that T, and Tareboth red cell points. If either both" red cell points or both whitecell points are indicated, OR gate 110 will produce a high output.

The same basic logic is performed by logic circuit S1, S2, and S4. Ahigh output from any one of the logic circuits S1 through S4 indicatesthat: the corresponding pointin the tag array 92 Le, points T, throughT, are of the same cell type as T Assuming that one or more of thepoints T through T are of the same typeas T the precedence of the pointor points must be determined. A precedence logic circuit shown by thedashed lines in FIG. 6 and identified by the reference numeral 112determines the precedence of the points in the tag array in thefollowing order: T, (from thepresent cell segment), T T and T (from theprevious cell segment).

The precedence logic shown within block 112 is employed to handle thespecific situation in which more than one of the outputs from the logiccircuits S1 through S4 is high. In this situation, it is necessary todetermine the first one in precedence.

The output from the precedence logic circuit 112 on output line 114 isONE (high) if there is no point in T T T or T which is of the same celltype as that of T and ZERO (low) if there is a point which is the sameas T However, if T, is the first point which is the same type as T theprecedence logic circuit 112 produces a high ONE output on output lead116 which actuates a corresponding gate 118. With gate 118 actuated, theparticular tag or number in T is gated onto bus 120 and back into pointT in the tag array.

If the particular point in T was not the same as that in T theprecedence logic circuit 112 next examines the cell type of the point inT,. A corresponding circuit is provided for the T point in the tag arraywith gate 122 being actuated by the output from the precedence logiccircuit 112 on output line 124. Thus, if the points T and T are of thesame type, and T and T are not of the same type, the cell number ofparticular tag in T is gated through gate 122 onto bus 120 and then intoT A similar arrangement is also provided for the tag array point Tthrough output line 126 and gate 128 and for tag array point T throughoutput line 1311 and gate 132.

If there is no point in the tag array which is of the same type as T theoutput on lead 114 from the precedence logic circuit will be high andthis output is fed to red and white cell counter AND gates 134 and 136,respectively. The second input for each AND gate is the correspondingcount red signal or count white signal obtained from the circuitry shownin FIG. 5. If the count red signal is present, AND gate 134 produces aONE output on line 138 which is used to increment the.

red blood cell counter to the next number. The output from AND gate 134is also used to actuate a gate 140 which gates this next red blood cellnumber from counter 97 onto bus 120 and thus into tag array point T Asimilar arrangement is provided for the white blood cell counter 95through AND gate output line 142 and gate 144.

The output from the precedence logic circuit 112 on line 114 is alsoapplied to a NEW number logic circuit shown by the dashed lines in FIG.6 and identified by the reference numeral 146. The NEW number logiccircuit 146 maintains a record of the assignment of a new number to astring of points on the present line of analysis. The present line isrepresented in part within the tag array by points T and T while theprevious line appears in part in the tag array points T T and T The NEWlogic circuit 146 is used to distinguish between two cases in whichpoints in the same object have been assigned different numbers. The twocases can be thought of in general terms as the sloping line case theU-shaped case.

In the first case, a portion of the particular object under analysisslopes gently upwardly in the direction of the scan. The slope isgradual enough so that three or more points are encountered which arenot contiguous to any point in the previously scanned line. Since thepresent line points (at least three or more) are not contiguous with thepoints in the previous line, the precedence logic, tag array, and theappropriate red or white cell counters will assign a new number to thepresent line points. However, the present line points are a part of thesame object as the previous line points. Thus, we have a situation inwhich the previous line points have been assigned one number while thepresent line points have been assigned another number although in factall of the points are part of the same obnumber. Upon subsequent scans,the system will recognize that the two upstanding legs which have beenassigned individual numbers are in fact all part of the one particularobject.

In both cases recognition occurs when points of the same cell type buthaving different numbers appear in points T and T in tag array 92.Although the slopingline and U-shaped cases appear the same to the tagarray 92, they must be distinguished and treated differ-. ently. In thecase of the sloping-line object, the present line tag or number will bechanged to the previous line tag or number by means of the circuitryshown in FIG. 7 and the appropriate red or white cell counter will bedecremented. In the case of the U-shaped object, the two tags or cellnumbers will be associated with each other for purposes of subsequentidentification and incorporation of the features stored under each tagor cell number.

These two cases are distinguished by means of the NEW number logiccircuit 146 which comprises OR gates 148 and 150, AND gates 152, 154,and 156, and Flip-Flop 158. The inputs to the NEW number logic circuit146 are: count red (CNTR) on line 166; count white (CNTW) on input line162; the output from the precedence logic circuit on line 114 whichrepresents an Assign-New-Number" signal; and, finally, a change signal(CI-IG) on line 164. The change signal is derived from the logic circuit166 shown in FIG. 7 in accordance with the following truth table:

The NEW Flip-Flop 158 is set whenever the Assign- New-Number signal onthe precedence output line 114 is ONE or high. The Assign-New-Numbersignal is applied as one input to AND gate 152. The second input to theAND gate 152 is provided by the output from OR gate 148. This input isONE (high) whenever a new number is assigned because either the countred signal or count white signal on OR gate input lines 160 and 162,respectively, is also high. The output from AND gate 152 is applied asone input to OR gate 150. Thus, if the output from AND gate 152 is highthe output from OR gate will also be high. The outputs from OR gate 148and 150 are ANDed by AND gate 154 thereby producing a high output online 168 which sets the NEW Flip-Flop 158.

The Flip-Flop 158 maintains itself in the set condition as long aseither a count red or a count white signal is present on lines 160 and162. If an object-tobackground (or cell-to-background) transitionoccurs, it can be seen that both the count red and count white signalswill be low on OR gate input lines 160 and 162 thereby allowing the NEWFlip-Flop 158 to reset. The Flip-Flop 158 also can be reset by a changesignal -(CI-IG) on line 164.

Referring now to FIG. 7 there is shown in block form additionalcircuitry that operates in conjunction with the tag array 92 and linedelay 94. For purposes of-clarity, this circuitry was omitted from FIG.6 and is shown in FIG. 7. Note that the tag array and line delays 92 and94, respectively, have been duplicated in FIG. 7.

For the sloping-line case, the circuitry shown in FIG. 7 (including thepreviously discussed logic circuit 166) performs the followingoperations: (1) changes the tag or cell number in T to the tag or cellnumber in T (2) decrements the appropriate red or white blood cellcounter; and, (3) when appropriate, changes the tag or cell numbers in Tand in the line delay 94 to the tag or cell number in T In the case ofthe U-shaped cell or object, the logic circuit 166 produces a PushNumbers signal identified in FIG. 5 by the abbreviation PUSH and, whenappropriate, changes tag or cell numbers in T T and the line delay 94 tothe tag or cell number in T The PUSH signal causes the cell tags in Tand T to be pushed onto a push down stack (not shown) in the main memory(FIG. 9). The change signal (CHG) from logic circuit 166 on line 170gates the T tag or cell number on bus 172 through gate 176 onto T Thetag or cell number on T bus 172 is also gated into T through gate 178.Operation of gate 178 is controlled by means of a logic circuit 180. Thetruth table for logic circuit 180 is as follows:

IN PUTS T T CHG OUTPUT It can be seen from the truth table that if T isequal to T the T number on bus 172 is gated through gate 178 into T Asimilar logic circuit 182 controls another gate 184 which gates the Tnumber on bus 172 into the first element of the line delay 94. Since theline delay 94 comprises a shift register having a predetermined numberof storage elements, the logic 182 and gate 184 is duplicated for apredetermined number of adjacent storage elements in the shift register94. This additional circuitry is represented in FIG. 7 by the continuingthree dots. The purpose of the logic associated with the shift registerline delay 94 is to correct the improperly numbered present line pointsin T T and the line delay 94. Note that these present points actuallyshould have the same number as the previous line point in T The logiccircuit 166 also generates a down count or counter decrement signal(DCNT) in accordance with the truth table set forth above. Thedown-count signal is applied as one input to two AND gates 186 and 188shown in FIG. 6. AND gate 186 controls the operation of the red bloodcell counter 97. The second input to AND gate 186 is the count redsignal (CNTR). In a similar manner AND gate 188 decrements the whiteblood cell counter 95.

There remains one special case which should be provided for the casewhen one or more cells is touching or overlapping an edge of the field.A cell which overlaps the edge of the field will be incomplete and thusnot suitable for analysis. This case is provided for by causing the scanand digitize circuitry to output black points during its horizontal andvertical retrace intervals. These points are the first that areencountered at the beginning of a scan of the field, and being black,they look like an object. These points are given the tag number ZERO.Any cell touching the field edge will appear to be part of the sameobject, and thus will also be assigned tag number ZERO. To simplify datahandling, special circuitry (not shown) prevents the storage of any datain main memory when the tag number is ZERO. Thus, all objectsoverlapping the fields edge are ignored.

Having described in detail the operation of the circuitry which assignsa cell tag to each of the identified cell segments in response to thecontrol signals and sample region classification signals as shown inFIGS. 6 and 7, I will now discuss the utilization of theseidentification numbers with respect to the scanned image data. Referringback to FIG. 4 for a moment, the Digitized Serial Data Signals A, B, andC' is applied to corresponding storage shift registers 1900, 190b, and190C. Each shift register has a corrcsponding line delay 192a, 19% and192a. The output from each delay is fed back into the correspondingshift register. The delay provided by the signal transit through thelower portion, as viewed in the drawing of shift registers 190 and theline delays 192 correspond to one line width of the scanned image 14.This delay is employed to synchronize the image data signal with thepreviously discussed control signals.

The output from each shift register on lines 194a, 1194b, and 1940 isapplied as one input to a background subtract circuit 196a, 196b, and1196c. The second input to the background circuit is the associatedbackground density output from histogrammer 40. The output from each ofthe background subtract circuits 196 is a six-bit digitized signalrepresenting the scanned image data with the background densitysubtracted therefrom. These outputs are identified as DATA-A. DATA-B andDATA-C.

' Referring now to FIG. 8, the partial cell features are compiled foreach of the identified and tagged cell segments. The full data signalsDATA-A, DATA-B, and DATA-C are inputted to white and red blood celldensity summing circuits. As shown in FIG. 8, a separate accumulator198a, 198b, and 1980 is provided for each data channel to sum thedensities of the white blood cell nucleus DATA-A, DATA-B, and DATA-C.Corresponding accumulators 200a, 200b, and 2006 are provided for thewhite blood cell cytoplasm data. Red blood cell density summation isprovided for data channels A and C by accumulators 202a. and 2020. TheDATA-A, DATA-B, and DATA-C information is gated into the appropriateaccumulators in accordance with the gating control signal count nucleus(CNTN), count cytoplasm (CNTC) and count red (CNTR). These sig' nals arederived from the control logic circuit 86 shown in FIG. 5.

The control signals are also used to gate either the appropriate tagnumber from the tag array block T into white blood cell tag register 204or red blood cell tag cell register 206. In addition, these controlsignals are also used to increment either nucleus, cytoplasm or redblood cell size counters 208, 210, and 212, respectively.

Looking now at the bottom portion of FIG. 8 there are shown three dualperimeter counters 214, 216, and 218 for the white blood cell nucleusperimeter, white blood cell cytoplasm perimeter, and red blood cellperimeter, respectively. Each counter sums the number of straight anddiagonal perimeter signals in each cell component type. The dual whiteblood cell nucleus perimeter counter 214 is incremented by the straightperimeter control signal (STN) and by the diagonal perimeter nucleuscontrol signal (DPB) which are obtained from control logic circuit 76shown in FIG. 5.

The dual cytoplasm perimeter counter 216 is incremented by the outputfrom two AND gates 218 and 220. AND gate 218 has as its input thestraight perimeter, white cytoplasm signal (STWC) which is derived fromcontrol logic 82 shown in FIG. and the inverted perimeter inhibit signal(PINI-I) which is derived from control logic circuit 86 shown in FIG. 5.

Referring back to the truth table for control logic circuit 86, it canbe seen that when the perimeter inhibit signal is low or ZERO and thestraight perimeter white cytoplasm signal is present, AND gate 218 willproduce an output which increments the straight perimeter segmentcounting portion of the dual cytoplasm perimeter counter 216. AND 220also utilizes the perimeter inhibit signal together with the diagonalperimeter, white cytoplasm control signal (DPWC) which is derived fromthe control logic circuit 82 shown in FIG. 5. Similar circuitry is alsoused for the dual red perimeter counter 218 through AND gates 222 and224. The corresponding control signals straight'perimeter red (SPR) anddiagonal perimeter red (DPR) are obtained from control logic circuit 84shown in FIG. 5.

Referring back for a moment to the tag array shown in FIGS. 6 and 7, ifthere are no cell points in the tag array blocks T and T (including abackground situation) and there are cell points in tag array T and T theconfiguration reflects the existence of a perimeter segment from aprevious cell on a previous line that was not detected by the system.This situation is handled by the circuitry shown at the very bottom ofFIG. 8. The cell tag or number from the T block of the tag array 92 isgated into an appropriate nucleus alternate number register 226, acytoplasm alternate number register 228 or a red blood cell alternatenumber register 230. The gating signals for the nucleus and cytoplasmalternate number register 226 and 228 comprise the control signalsprevious row perimeter, nucleus (PRN) and previous row, white cytoplasm(PRWC) which are obtained from control logic circuits 76 and 82,respectively, shown in FIG. 5.

The red blood cell alternate number register number 230 is controlled bythe gating signals previous row, red cell (PRR) which is derived fromcontrol logic circuit 84 shown in FIG. 5. These control signals are alsoused to increment corresponding alternate perimeter counters 232, 234,and 236.

Looking now at FIG. 9, the white blood cell portion of the nucleus andcytoplasm counters, accumulators and registers have been duplicated inFIG. 9 with the same reference numerals being used to identify likecomponents. FIG. 9 illustrates the outputs from each of these circuitcomponents. Note that the inputs shown in FIG. 8 have been omitted fromFIG. 9. Furthermore, the entire red blood cell portion has been omittedfrom FIG. 9. However, it should be understood that the same basiccircuitry is employed for the handling of the red blood cell data.

FIG. 9 illustrates the use of each cell tag to sequentially compilecomplete cell features from the partial cell features of each identifiedcell segment having the same cell tag. The outputs from the white bloodcell nucleus size counter 208, cytoplasm size counter 210, densityaccumulators 198a through 1980 and 200a through 2000, nucleus andcytoplasm perimeter counters 214 and 216, respectively, are shifted intoa buffer memory 238 in response to a store white cell signal (STW). Theappropriate tag or cell number from the white blood cell register 204 isalso shifted into the buffer memory at the same time. The contents ofthe buffer memory are added into a main memory 240 (which includes acontroller) in locations determined by the cell tag. In this way all thepartial features having the same cell tag are added to the samelocations to produce the complete features for the tagged cell. The mainmemory controller controls the gating of the buffer memory data into themain memory and adds the buffer contents to the previous contents in themain memory. After a short delay the WBC counters and accumulators arecleared by a clear" signal produced by delay circuit 242.

It should be noted at this point that the red blood cell information isprocessed in the same manner through a buffer memory (not shown) intothe main memory and controller 240.

The contents of the alternate perimeter counters 232 and 234 for thenucleus and cytoplasm, respectively, are also shifted into anotherbuffer memory 244. In a similar manner, the tag or cell numberscontained in the alternate number registers 226 and 228 are shifted intothe buffer memory 244. The alternate perimeter and alternate number datais shifted into the buffer memory 244 in response to the store previousrow, nucleus (SPRN) signal or the store previous row, white cytoplasm(SRWC) signal which are obtained from the FIG. 3 logiccircuits 76 and82, respectively. These two signals are applied as one input to an ANDgate 246 whose output controls the shifting of the alternate perimeterand alternate number data into the buffer memory 244. The second inputto AND gate 246 is provided by the output of an OR gate 248 whose inputscomprise the outputs of the nucleus alternate number register 226 andthe cytoplasm alternate number register 228.

The operation of the alternate perimeter circuitry shown in the bottomof FIG. 9 can best be understood by looking back for a moment at FIGS. 5and 6. Assume that the five block delay arrays 66, 68, and in FIG. 5 andthe tag array 92 shown in FIG. 6 contain nu clear points in blocksnumbers 4 and 5, e.g. T, and T while the block numbers 1, 2, and 3contain no nuclear points. In this situation, it is clear that aperimeter segment has been encountered. I-Iowever, let us assume thatall five blocks have nuclear points, but the points in the scanned imagejust below points 4 and 5 have background points (this will berecognized on the next line scan). The perimeter segment will berecognized only when the points in T and T are shifted through to thetag array T and T and T, and the background points just below points Tand T are placed in T and T It will be appreciated that at this time itis too late to recognize this special case for the perimeter segment bymeans of the regular circuitry. The additional alternate perimetercircuitry shown in FIGS. 8 and 9 is employed to determine and compilethe extra perimeter segments produced in this specific situation.

Referring back to FIG. 9, the contents of the buffer memory are addedinto the main memory in response to the main memory controller. After asuitable delay produced by delay circuit 250, the alternate perimetercounters are cleared by the "clear-A signal.

It remains to describe the operation of a one-bit LINK register 252 inFIG. 8. The LINK is set by logic

1. A method of analyzing an illuminated subject comprising the stepsof:
 1. producing a first signal representing a first predeterminedwavelength band of the subject modified illumination at a region in saidsubject;
 2. producing a second signal representing a secondpredetermined wavelength band of the subject modified illumination atsaid region, said first and second wavelength bands being selected toproduce a differential contrast between said region and at least oneother region in said subject; and,
 3. algebraically combining withthresholding said first and second signals to classify said subjectregion in at least one of a predetermined number of categories.
 2. meansfor producing first, second and third raster scanned signalsrepresenting corresponding first, second and third predeterminedwavelength bands of the sample modified light, said first, second andthird wavelength bands being selected to produce a differential contrastbetween at least two different regions in said sample;
 2. means forproducing a first signal representing a first wavelength band in theorder of 570-600 nm. of the blood sample modified light at a region insaid sample;
 2. means for producing a first, second and third rasterscanned signal representing corresponding first, second and thirdpredetermined wavelength bands of the sample modified light, said first,second and third wavelength bands being selected to produce adifferential contrast between at least two different regions in saidsample;
 2. means for illuminating the stained blood cell sample withlight which is modified by said blood cell sample;
 2. said firstpredetermined wavelength band is in the order of 500-530 n.m.;
 2. meansfor producing a first signal representing a first predeterminedwavelength band of the blood cell sample modified light at a region insaid sample;
 2. assigning a sample tag to each of said identified samplesegments; and,
 2. producing a scanned signal representing the samplemodified light;
 2. means thresholding the scanned signal to produce acontrol signal;
 2. means for producing a first, second and third rasterscanned signal representing corresponding first, second and thirdpredetermined wavelength bands of the sample modified light, said first,second and third wavelength bands being selected to produce adifferential contrast between at least two different regions in saidsample;
 2. producing first and second raster scanned signalsrepresenting corresponding first and second predetermined wavelengthbands of the sample modified light, said first and second wavelengthbands being selected to produce a differential contrast between at leasttwo different regions in said sample;
 2. producing first and secondsignals representing corresponding first and second predeterminedwavelength bands of the sample modified light, said first and secondwavelength bands being selected to produce a differential contrastbetween at least two different regions in said sample;
 2. producing afirst, second and third raster scanned signal representing correspondingfirst, second and third predetermined wavelength bands of the samplemodified light, said first, second and third wavelength bands beingselected to produce a differential contrast between at least twodifferent regions in said sample;
 2. said first predetermined wavelengthband is in the order of 570-600 n.m.;
 2. means for producing first,second and third raster scanned signals representing correspondingfirst, second and third predetermined wavelength bands of the samplemodified light, said first, second and third wavelength bands beingselected to produce a differential contrast between at least twodifferent regions in said sample;
 2. means for producing first andsecond signals representing corresponding first and second predeterminedwavelength bands of the sample modified light, said first and secondwavelength bands being selected to produce a differential contrastbetween at least two different regions in said sample;
 2. means forproducing a first, second and third raster scanned signal representingcorresponding first, second and third predetermined wavelength bands ofthe sample modified light, said first, second and third wavelength bandsbeing selected to produce a differential contrast between at least twodifferent regions in said sample;
 2. illuminating said staIned bloodsample with light which is modified by the stained blood sample; 2.means for producing a first signal representing a first wavelength bandin the order of 570-600 nm. of the blood sample modified light at aregion in said sample;
 2. means for producing a first signalrepresenting a first predetermined wavelength band of the blood samplemodified light at a region in said sample;
 2. means for producing asecond signal representing a second predetermined wavelength band of thesubject modified illumination at said region, said first and secondwavelength bands being selected to produce a differential contrastbetween said region and at least one other region in said subject; and,2. means for illuminating the stained blood sample with light which ismodified by said blood cell sample;
 2. said first predeterminedwavelength band is in the order of 570-600 n.m.;
 2. said firstpredetermined wavelength band is in the order of 570-600 n.m.; 2.illuminating stained blood sample with light which is modified by thestained blood sample;
 2. means for producing a first signal representinga first predetermined wavelength band of the blood sample modified lightat a region in said sample;
 2. producing first and second scannedsignals representing corresponding first and second predeterminedwavelength bands of the sample modified light, said first and secondwavelength bands being selected to produce a differential contrastbetween at least two different regions in said sample;
 2. means forproducing a first, second and third raster scanned signal representingcorresponding first, second and third predetermined wavelength bands ofthe sample modified light, said first, second and third wavelength bandsbeing selected to produce a differential contrast between at least twodifferent regions in said sample;
 2. means for producing a first signalrepresenting a first predetermined wavelength band of the blood samplemodified light at a region in said sample;
 2. means for producing firstand second scanned signals representing corresponding first and secondpredetermined wavelength bands of the sample modified light, said firstand second wavelength bands being selected to produce a differentialcontrast between at least two different regions in said sample;
 2. meansfor assigning a sample tag to each of said identified sample segments;and
 2. producing first and second raster scanned signals representingcorresponding first and second predetermined wavelength bands of thesample modified light, said first and second wavelength bands beingselected to produce a differential contrast between at least twodifferent regions in said sample;
 2. producing a second signalrepresenting a second predetermined wavelength band of the subjectmodified illumination at said region, said first and second wavelengthbands being selected to produce a differential contrast between saidregion and at least one other region in said subject; and,
 2. A methodof particle analysis comprising the steps of:
 2. producing a firstsignal representing a first predetermined wavelength band of theparticle modified light at a region in said particle;
 2. producing afirst signal representing a first predetermined wavelength band of theblood cell sample modified light at a region in said sample; 2.producing a first signal representing a first predetermined wavelengthband of the blood sample modified light at a region in said sample; 2.illuminating the stained blood cell sample with light which is modifiedby said blood cell sample;
 2. illuminating the stained blood sample withlight which is modified by said blood cell sample;
 2. illuminating saidstained blood sample with light which is modified by the blood cellsample;
 2. illuminating the stained blood cell sample with light whichis modified by the sample;
 2. means for assigning a sample tag to eachof said identified sample segments; and,
 2. illuminating the stainedblood cell sample with light which is modified by the sample; 2.assigning a sample tag to each of said identified sample segments; and,2. illuminating said stained blood sample with light which is modifiedby the stained blood sample;
 2. means for producing a first signalrepresenting a first predetermined wavelength band of the blood cellsample modified light at a region in said sample;
 2. producing first andsecond raster scanned signals representing corresponding first andsecond predetermined wavelength bands of the sample modified light, saidfirst and second wavelength bands being selected to produce adifferential contrast between at least two different regions in saidsample;
 2. thresholding the scanned signal to produce a control signal;2. means for producing first and second raster scanned signalsrepresenting corresponding first and second predetermined wavelengthbands of the sample modified light, said first and second wavelengthbands being selected to produce a differential contrast between at leasttwo different regions in said sample;
 2. means for producing a firstsignal representing a first predetermined wavelength band of the stainedblood cell sample modified light at a region in said sample;
 2. meansfor producing a first, second and third raster scanned signalrepresenting corresponding first, second and third predeterminedwavelength bands of the sample modified light, said first, second andthird wavelength bands being selected to produce a differential contrastbetween at least two different regions in said sample;
 2. means forproducing first, second and third raster scanned signals representingcorresponding first, second and third predetermined wavelength bands ofthe sample modified light, said first, second and third wavelength bandsbeing selected to produce a differential contrast between at least twodifferent regions in said sample;
 2. illuminating the stained blood cellsample with light which is modified by the sample;
 2. producing first,second and third raster scanned signals representing correspondingfirst, second and third predetermined wavelength bands of the samplemodified light, said first, second and third wavelength bands beingselected to produce a differential contrast between at least twodifferent regions in said sample;
 3. producing first, second and thirdraster scanned signals representing corresponding first, second andthird predetermined wavelength bands of the sample modified light, saidfirst, second and third wavelength bands being selected to produce adifferential contrast between at least two different regions in saidsample;
 3. means for digitizing said first, second and third rasterscanned signals to produce corresponding first, second and thirddigitized serial data signals;
 3. means for algebraically combining withthresholding said first and second signals to produce sample regionclassification signals;
 3. means for producing a second signalrepresenting a second predetermined wavelength band of the blood samplemodified light at said region, said first and second wavelength bandsbeing selected to produce a differential contrast between said regionand one other region in said blood cell sample; and,
 3. means forthresholding said first, second and third raster scanned signals toproduce corresponding first, second and third thresholded signals; 3.means for producing a second signal representing a second predeterminedwavelength band of the stained blood cell sample modified light at saidregion;
 3. utilizing said control signal to identify sample segments inthe scanned signal;
 3. thresholding said first and second raster scannedsignals to produce corresponding first and second thresholded signals;3. means for producing a second signal representing a second wavelengthband in the order of 500-530 nm. of the blood sample modified light atsaid region;
 3. means for producing a second signal representing asecond predetermined wavelength band of the blood cell sample modifiedlight at said region;
 3. A method of blood cell analysis comprising thesteps of:
 3. producing a first signal representing a first wavelengthband in the order of 570-600 n.m. of the blood sample modified light ata region in said sample;
 3. utilizing each sample tag to sequentiallycompile complete sample features from the partial sample features ofeach identified sample segment having the same sample tag.
 3. meansutilizing each sample tag for sequentially compiling complete samplefeatures from the partial sample features of each identified samplesegment having the same sample tag.
 3. producing a first, second andthird raster scanned signal representing corresponding first, second andthird predetermined wavelength bands of the sample modified light, saidfirst, second and third wavelength bands being selected to produce adifferential contrast between at least two different regions in saidsample;
 3. producing a first, second and third raster scanned signalrepresenting corresponding first, second and third predeterminedwavelength bands of the sample modified light, said first, second andthird wavelength bands being selected to produce a differential contrastbetween at least two different regions in said sample;
 3. producing afirst signal representing a first wavelength band in the order of500-530 nm. of the blood sample modified light at a region in saidsample;
 3. producing a first signal representing a first predeterminedwavelength band of the stained blood sample modified light at a regionin said sample;
 3. producing a first signal representing a firstpredetermined wavelength band of the stained blood cell sample modifiedlight at a region in said sample;
 3. producing a second signalrepresenting a second predetermined wavelength band of the blood samplemodified light at said region, said first and second wavelength bandsbeing selected to produce a differential contrast between said regionand at least one other region in said blood cell sample; and, 3.producing a second signal representing a second predetermined wavelengthband of the blood sample modified light at said region, said first andsecond wavelength bands being selected to produce a differentialcontrast between said region and at least one other region in said bloodcell sample; and,
 3. producing a second signal representing a secondpredetermined wavelength band of the particle modified light at saidregion, said first and second wavelength bands being selected to producea differential contrast between said region and at least one otherregion in said particle sample; and,
 3. algebraically combining withthresholding said first and second signals to classify said subjectregion in at least one of a predetermined number of categories.
 3. meansutilizing each sample tag for sequentially compiling complete samplefeatures from the partial sample features of each identified samplesegment having the same sample tag.
 3. means for algebraically combiningwith thresholding said first and second scanned signals to producesample region classification signals;
 3. means for producing a secondsignal representing a second predetermined wavelength band of the bloodsample modified light at said region, said first and second wavelengthbands being selected to produce a differential contrast between saidregion and at least one other region in said blood cell sample;
 3. meansfor digitizing said first, second and third raster scanned signals toproduce corresponding first, second and third digitized serial datasignals;
 3. algebraically combining with thresholding said first andsecond signals to produce control signals;
 3. means for producing asecond signal representing a second predetermined wavelength band of theblood sample modified light at said region, said first and secondwavelength bands being selected to produce a differential contrastbetween said region and at least one other region in said blood cellsample;
 3. said second predetermined wavelength band is in the order of500-530 n.m.;
 3. producing a A signal representing a first wavelengthband in the order of 570-600 n.m. of the blood sample modified light ata region in said sample;
 3. said second predetermined wavelength band isin the order of 500-530 n.m.;
 3. means for algebraically combining withthresholding said first and second signals to classify said subjectregion in at least one of a predetermined number of categories. 3.algebraically combining with thresholding said first and second scannedsignals to produce sample region classification signals;
 3. producing afirst signal representing a first wavelength band in the order of570-600 nm. of the blood sample modified light at a region in saidsample;
 3. means for digitizing said first, second and third rasterscanned signals to produce corresponding first, second and thirddigitized serial data signals;
 3. means for thresholding said first,second and third raster scanned signals to produce corresponding first,second and third threshold signals to produce sample regionclassification signals;
 3. said second predetermined wavelength band isin the order of 500-530 n.m.;
 3. algebraically combining withthresholding said first and second signals to produce sampLe regionclassification signals;
 3. thresholding said first, second and thirdraster scanned signals to produce corresponding first, second and thirdthresholded signals;
 3. algebraically combining with thresholding saidfirst and second signals to produce sample region classificationsignals;
 3. means for algebraically combining with thresholding saidfirst, second and third raster scanned signals to produce sample regionclassification signals;
 3. means responsive to said control signal foridentifying sample segments in the scanned signal;
 3. thresholding thescanned signal to produce a control signal;
 3. utilizing each sample tagto sequentially compile complete sample features from the partial samplefeatures of each identified sample segment having the same sample tag.3. means for algebraically combining with thresholding said first andsecond signals to produce sample region classification signals; 3.thresholding said first, second and third raster scanned signals toproduce corresponding first, second and third thresholded signals; 3.means for producing a first signal representing a first predeterminedwavelength band of the stained blood sample modified light at a regionin said sample;
 3. said second predetermined wavelength band is in theorder of 400-420 n.m.; and
 3. means for producing a first signalrepresenting a first predetermined wavelength band of the stained bloodcell sample modified light at a region in said sample;
 3. means forproducing a second signal repreSenting a second predetermined wavelengthband of the blood sample modified light at said region, said first andsecond wavelength bands being selected to produce a differentialcontrast between said region and at least one other region in said bloodcell sample; and,
 3. means for thresholding said first, second and thirdraster scanned signals to produce corresponding first, second and thirdthresholded signals;
 3. means for algebraically combining withthresholding said first, second and third signals to produce sampleregion classification signals;
 3. means for producing a second signalrepresenting a second wavelength band in the order of 500-530 nm. of theblood sample modified light at said region;
 4. means for producing athird signal representing a third wavelength Band in the order of400-420 nm. of the blood sample modified light at said region, saidfirst, second and third wavelength bands producing a differentialcontrast between said region and at least one other region in said bloodcell sample;
 4. further comprising means for thresholding each of saidfirst and second signals to produce corresponding binary first andsecond thresholded signals; and,
 4. means for algebraically combiningsaid first, second and third thresholded signals to produce sampleregion classification signals;
 4. means for algebraically combining saidsample region classification signals to produce control signals; 4.means for producing a second signal representing a second predeterminedwavelength band of the stained blood cell sample modified light at saidregion;
 4. means for algebraically combining with thresholding saidfirst and second signals to classify said region in at least one of apredetermined number of categories.
 4. means for producing a thirdsignal representing a third wavelength band in the order of 400-420 nm.of the blood sample modified light at said region, said first, secondand third wavelength bands producing a differential contrast betweensaid region and at least one other region in said blood cell sample;and,
 4. means responsive to said control signal for compiling partialsample features from the scanned signal on a line-by-line basis for eachsaid identified sample segment; and,
 4. means for algebraicallycombining said sample region classification signals to produce firstcontrol signals;
 4. algebraically combining said sample regionclassification signals to produce control signals;
 4. delaying saidcontrol signal to re-establish its vertical connection;
 4. said thirdpredetermined wavelength band is in the order of 400-420 n.m.;
 4. saidthird predetermined wavelength band is in the order of 400-420 n.m.; 4.means for histogramming said first, second and third digitized serialdata signals to produce at least one threshold level for each of saiddigitized serial data signals;
 4. utilizing said sample regionclassification signals to compile partial sample features from the firstand second signals for each sample region; and,
 4. said thirdpredetermined wavelength band is in the order of 400-420 n.m.;
 4. meansfor producing a second signal representing a second predeterminedwavelength band of the stained blood sample modified light at saidregion, said first and second wavelength bands being selected to producea differential contrast between said region and at least one otherregion in said blood cell sample;
 4. producing a B signal representing asecond wavelength band in the order of 500-530 n.m. of the blood samplemodified light at said region;
 4. algebraically combining said first,second and third threshold signals to produce sample regionclassification signals;
 4. means for algebraically combining withthresholding said first and second signals to classify said region as abackground, a red blood cell or a white blood cell.
 4. algebraicallycombining said first and second thresholded signals to produce sampleregion classification signals;
 4. utilizing said control signals toidentify sample segments in the raster scanned signals;
 4. means foralgebraically combining with thresholding said first, second and thirddigitized serial data signals to produce sample region classificationsignals;
 4. means responsive to said sample region classificationsignals for identifying sample segments in the scanned signals;
 4. meansresponsive to said sample region classification signals for compilingpartial sample features from the first and second signals for eachsample region; and,
 4. algebraically combining with thresholding saidfirst and second signals to classify said particle region in at leastone of a predetermined number of categories.
 4. algebraically combiningwith thresholding said first and second signals to classify said regionin at least one of a predetermined number of categories.
 4. The methodof claim 3 further characterized by staining said blood cell samplebefore illuminating the sample.
 4. algebraically combining withthresholding said first and second signals to classify said region as abackground, a red blood cell or a white blood cell.
 4. producing asecond signal representing a second predetermined wavelength band of thestained blood cell sample modified light at said region;
 4. producing asecond signal representing a second predetermined wavelength band of thestained blood sample modified light at said region, said first andsecond wavelength bands being selected to produce a differentialcontrast between said region and at least one region in said blood cellsample;
 4. digitizing said first, second and third raster scannedsignals to produce corresponding first, second and third digitizedserial data signals;
 4. thresholding said first, second and third rasterscanned signals to produce corresponding first, second and thirdthresholded signals;
 4. utilizing said sample region classificationsignals to identify sample segments in the scanned signals;
 4. producinga second signal representing a second wavelength band in the order of400-420 nm. of the blood sample modified light at said region, saidfirst and second wavelength band producing a differential contrastbetween said region and at least one other region in said stained bloodcell sample;
 4. utilizing said control signal to compile partial samplefeatures from the scanned signal on a line-by-line basis for each saididentified sample segment; and,
 4. means for producing a third signalrepresenting a third predetermined wavelength band of the stained bloodsample modified light at said region, said first, second and thirdwavelength bands being selected to produce a differential contrastbetween said region and at least one other region in said blood cellsample; and,
 4. producing a second signal representing a secondwavelength band in the order of 500-530 nm. of the blood sample modifiedlight at said region;
 4. means for thresholding said first, second andthird digitized serial data signals to produce first, second and thirdthresholded signals;
 4. means for algebraically combining said first,second and third thresholded signals to produce sample regionclassification signals;
 4. means for algebraically combining said firstand second signals; and,
 4. means for algebraically combining saidfirst, second and third threshold signals to produce sample regionclassification signals;
 4. producing a second signal representing asecond wavelength band in the order of 500-530 n.m. of the blood samplemodified light at said region;
 4. means for algebraically combining saidsample region classification signals to produce control signals; 4.digitizing said first, second and third raster scanned signals toproduce corresponding first, second and third digitized serial datasignals;
 4. algebraically combining said first, second and thirdthresholded signals to produce sample region classification signals; 4.thresholding each of said first and second signals to producecorresponding first and second thresholded signals; and,
 4. means forproducing a third signal representing a third predetermined wavelengthband of the blood sample modified light at said region, said first,second and third wavelength band being selected to produce adifferential contrast between said region and at least one other regionin said blood cell sample; and,
 5. means for algebraically combiningsaid binary first and second thresholded signals to classify said regionas a background, a red blood cell or a white blood cell, said binarythresholded signals being algebraically combined as follows: 5.algebraically combining said sample region classification signals toproduce control signals;
 5. histogramming said first, second and thirddigitized serial data signals to produce at least one threshold levelfor each of said digitized serial data signals;
 5. means responsive tosaid control signals for identifying cell segments in the raster scannedsignals;
 5. producing a third signal representing a third wavelengthband in the order of 400-420 n.m. of the blood sample modified light atsaid region, said first, second and third wavelength bands producing adifferential contrast between said region and at least one other regionin said stained blood cell sample;
 5. said first and third signals arethresholded to produce corresponding binary first and third thresholdedsignals;
 5. means for algebraically combining said sample regionclassification signals to produce first control signals;
 5. means foralgebraically combining said first, second and third thresholded signalsto produce sample region classification signals;
 5. thresholding each ofsaid first and second signals to produce corresponding binary first andsecond thresholded signals; and,
 5. utilizing said sample regionclassification signals to compile partial sample features from thescanned signals on a line-by-line basis for each said identified samplesegment; and,
 5. thresholding said first, second and third digitizedserial data signals to produce first, second and third thresholdedsignals;
 5. means responsive to said sample region classificationsignals for compiling partial sample features from the scanned signalson a line-by-line basis for each said identified sample segment; and, 5.thresholding each of said first and second signals to producecorresponding first and second thresholded signals; and,
 5. producing athird signal representing a third predetermined wavelength band of thestained blood sample modified light at said region, said first, secondand third wavelength band being selected to produce a differentialcontrast between said region and at least one other region in said bloodcell sample;
 5. A method of blood cell analysis comprising the steps of:5. means for thresholding said first, second and third digitized serialdata signals using said threshold level signals to produce correspondingfirst, second and third thresholded signals;
 5. means for algebraicallycombining said first and second thresholded signals to classify saidregion as a background, a red blood cell or a white blood cell.
 5. meansfor thresholding each of said first, second, and third signals toproduce corresponding binary first, second and third thresholdedsignals; and,
 5. means for algebraically combining with threshholdingsaid first, second and third signals to classify said region as abackground, a red blood cell or a white blood cell.
 5. utilizing saidcontrol signals to identify cell segments in the raster scanned signals;5. producing a C signal representing a third wavelength band in theorder of 400-420 n.m. of the blood sample modified light at said region,said first, second and third wavelength bands producing a differentialcontrast between said region and at least one other region in saidstained blood cell sample;
 5. utilizing said control signals to compilepartial sample features from the raster scanned signals on aline-by-line basis for each said identified sample segment;
 5. means foralgebraically combining said sample region classification signals toproduce first control signals;
 5. means for thresholding saidalgebraically combined signal and at least one of said first and secondsignals to classify said region as a background, a red blood cell or awhite blood cell.
 5. means for compiling complete sample features fromsaid partial sample features.
 5. said first, second and third signalsare thresholded to produce corresponding binary first, second and thirdthresholded signals; and,
 5. means for algebraically combining saidfirst and second signals; and,
 5. compiling complete sample featuresfrom said partial sample features.
 5. said first, second, and thirdsignals are thresholded to produce corresponding binary first, secondand third thresholded signals; and,
 5. compiling complete samplefeatures from said partial sample features.
 5. producing a third signalrepresenting a third wavelength band in the order of 400-420 nm. of theblood sample modified light at said region, said first, second and thirdwavelength bands producing a differential contrast between said regionand at least one other region in said stained blood cell sample; 5.means for producing a third signal representing a second predeterminedwavelength band of the stained blood cell sample modified light at saidregion, said first, second and third wavelength band being selected toproduce a differential contrast between said region and at least oneother region in said blood cell sample;
 5. algebraically combining saidfirst, second and third thresholded signals to produce sample regionclassification signals;
 5. algebraically combining said sample regionclassification signals to produce first control signals;
 5. utilizingsaid control signal to identify sample segments in the scanned signal;5. means for delaying said sample region classification signals tore-establish their vertical connection;
 5. means for compiling completesample features from said partial sample features.
 5. means foralgebraically combining said first, second and third signals withthresholding to classify said region as a background, a red blood cellnucleus, a red blood cell cytoplasm, said signals being algebraicallycombined as follows:
 5. algebraically combining said sample regionclassification signals to produce cOntrol signals;
 5. means for delayingsaid sample region classification signals to re-establish their verticalconnection;
 5. means for algebraically combining said sample regionclassification signals to produce control signals;
 5. means foralgebraically combining with thresholding said first, second and thirdsignals to classify said region as a background, a red blood cell or awhite blood cell.
 5. algebraically combining said sample regionclassification signals to produce first control signals;
 6. means fordelaying said sample region classification signals to re-establish theirvertical connection;
 6. thresholding said first, second and thirddigitized serial data signals using said threshold level signals toproduce corresponding first, second and third thresholded signals; 6.means for algebraically combining with thresholding said first, secondand third signals to classify said region as a background, a red bloodcell or a white blood cell.
 6. delaying said sample regionclassification signals to re-establish their vertical connection; 6.means for utilizing said control signals to identify cell segments inthe raster scanned signals;
 6. means for algebraically combining thevertically connected sample region classification signals to producesecond control signals;
 6. utilizing said control signal to compilepartial sample features from the scanned signal on a line-by-line basisfor each said identified sample segment;
 6. delaying said sample regionclassification signals to re-establish their vertical connection; 6.utilizing said control signals to identify cell segments in the rasterscanned signals;
 6. algebraically combining said sample regionclassification signals to produce first control signals;
 6. said binarythresholded signals are algebraically combined as follows:
 6. means foralgebraically combining said binary first, second and third thresholdedsignals to classify said region as a background, a red blood cellnucleus, a red blood cell cytoplasm, white blood cell nucleus or a whiteblood cell cytoplasm, said binary thresholded signals beingalgebraically combined as follows:
 6. means for thresholding saidalgebraically combined signal and at least one of said first and secondsignals to classify said region as a background, a red blood cell or awhite blood cell.
 6. said binary thresholded signals are algebraicallycombined as follows:
 6. generating sample tags;
 6. means for delayingsaid sample region classification signals to re-establish their verticalconnection;
 6. thresholding said A and C signals to producecorresponding binary A and C thresholded signals;
 6. utilizing saidcontrol signals to compile partial cell features from the raster scannedsignals on a line-by-line basis for each said identified cell segment;6. means for algebraically combining said first, second and thirdthresholded signals to produce sample region classification signals; 6.A method of blood cell analysis comprising the steps of:
 6. thresholdingeach of said first, second and third signals to produce correspondingfirst, second, and third thresholded signals; and,
 6. algebraicallycombining said first and second thresholded signals to classify saidregion as a background, a red blood cell or a white blood cell.
 6. meansfor compiling complete sample features from said partial samplefeatures.
 6. compiling complete sample features from said partial samplefeatures.
 6. algebraically combining said binary first and secondthresholded signals to classify said region as a background, a red bloodcell or a white blood cell, said binary thresholded signals beingalgebraically combined as follows:
 6. means for algebraically combiningsaid sample region classification signals to produce first controlsignals;
 6. thresholding each of said first, second, and third signalsto produce corresponding binary first, second and third thresholdedsignals; and,
 6. means for delaying said sample region classificationsignals to re-establish their vertical connection;
 6. algebraicallycombining said first, second and third thresholded signals to producesample region classification signals;
 6. means for delaying said sampleregion classification signals to re-establish their vertical connection;6. said second signal is thresholded at two different thresholds toproduce binary second and second prime thresholded signals; and, 6.thresholding each of said first, second and third signals to producecorresponding binary first, second and third thresholded signals; and,6. means responsive to said control signals for compiling partial cellfeatures from the raster scanned signals on a line-by-line basis foreach said identified cell segment;
 7. means for generating cell tags; 7.means for utilizing said first control signals to identify cell segmentsin the raster scanned signals;
 7. utilizing said control signals toidentify cell segments in the raster scanned signals;
 7. means foralgebraically combining the vertically connected sample regionclassification signals to produce second control signals;
 7. means foralgebraically combining the vertically connected sample regionclassification signals to produce second control signals; 7.algebraically combining said binary first, second and third thresholdedsignals to classify said region as a background, a red blood cellnucleus, a red blood cell cytoplasm, a white blood cell nucleus or awhite blood cell cytoplasm, said binary thresholded signals beingalgebraically combined as follows:
 7. utilizing said control signals tocompile partial cell features from the raster scanned signals on aline-by-line basis for each said identified cell segment;
 7. A method ofblood cell analysis comprising the steps of:
 7. means for algebraicallycombining said sample region classification signals to produce firstcontrol signals;
 7. algebraically combining said first, second and thirdthresholded signals to classify said region as a background, a red bloodcell or a white blood cell.
 7. algebraically combining said first,second and third thresholded signals to produce sample regionclassification signals;
 7. thresholding said B signals at two differentthresholds to produce binary B and B'' thresholded signals; and, 7.generating cell tags;
 7. means for algebraically combining thevertically connected sample region classification signals to producesecond control signals;
 7. delaying said sample region classificationsignals to re-establish their vertical connection;
 7. means for delayingsaid sample region classification signals to re-establish their verticalconnection;
 7. algebraically combining the vertically connected sampleregion classification signals to produce second control signals; 7.means for utilizing said control signals to compile partial cellfeatures from the raster scanned signals on a line-by-line basis foreach said identified cell segment;
 7. assigning a sample tag to each ofsaid identified sample segments; and,
 7. algebraically combining saidbinary first, second and third thresholded signals to classify saidregion as a background, a red blood cell, a white blood cell nucleus ora white blood cell cytoplasm, said binary thresholded signals beingalgebraically combined as follows:
 7. said binary thresholded signalsare algebraically combined as follows:
 7. algebraically combining saidsample region classification signals to produce first control signals;7. generating sample tags;
 7. means for utilizing said control signalsto identify cell segments in the raster scanned signals;
 8. means forutilizing said control signals to compile partial cell features from theraster scanned signals on a line-by-line basis for each said identifiedcell segment;
 8. delaying said sample region classification signals tore-establish their vertical connection;
 8. means for utilizing saidfirst and second control signals to compile partial cell features fromthe raster scanned signals on a line-by-line basis for each saididentified cell segment;
 8. means for generating cell tags; 8.algebraically combining the vertically connected sample regionclassification signals to produce second control signals;
 8. meansresponsive to said first control signals for identifying cell segmentsin the raster scanned signals;
 8. utilizing said first control signalsto identify cell segments in the raster scanned signals; 8.algebraically combining said A, B, B'', and C binary thresholded signalsto classify said region in a predetermined category, said binarythreshold signals being algebraically combined as follows:
 8. assigninga sample tag to each of said identified sample segments; and, 8.algebraically combining said sample region classification signals toproduce first control signals;
 8. The method of claim 7 furthercharacterized by algebraically combining said first, second and thirdthresholded signals to classify said region as a background, a red bloodcell, a white blood cell nucleus or as a white blood cell cytoplasm. 8.means for delaying said sample region classification signals tore-establish their vertical connection;
 8. means for utilizing saidfirst control signals to identify cell segments in the raster scannedsignals;
 8. generating cell tags;
 8. means for algebraically combiningthe vertically connected sample region classification signals to producesecond control signals;
 8. assigning a cell tag to each of saididentified cell segments; and,
 8. means for utilizing said first controlsignals to identify cell segments in the digitized serial data signals;8. utilizing said control signals to compile partial cell features fromthe raster scanned signals on a line-by-line basis for each saididentified cell segment;
 8. means for assigning a cell tag to each ofsaid identified cell segments in response to said control signals andsaid sample region classification signals; and,
 8. utilizing each sampletag to sequentially compile complete sample features from the partialsample features of each identified sample segment having the same sampletag.
 9. means utilizing each cell tag for sequentially compilingcomplete cell features from the partial cell features of each identifiedcell segment having the same cell tag.
 9. generating cell tags;
 9. meansfor utilizing said first and second control signals to compile partialcell features from the digitized serial data signals on a line-by-linebasis for each said identified segment;
 9. utilizing each cell tag tosequentially compile complete cell features from the partial cellfeatures of each identified cell segment having the same cell tag. 9.means for generating cell tags
 9. means for utilizing said first controlsignals to identify cell segments in the digitized serial data signals;9. assigning a cell tag to each of said identified cell segment inresponse to said control signals and said sample region classificationsignals; and,
 9. means for algebraically combining the verticallyconnected sample region classification signals to produce second controlsignals;
 9. A method of blood cell analysis comprising the steps of: 9.delaying said sample region classification signals to re-establish theirvertical connection;
 9. utilizing each sample tag to sequentiallycompile complete sample features from the partial sample features ofeach identified sample segment having the same sample tag.
 9. meansresponsive to said first and second control signals for compilingpartial cell features from the raster scanned signals on a line-by-linebasis for each said identified cell segment;
 9. utilizing said firstcontrol signals to identify cell segments in the raster scanned signals;9. means for utilizing said first and second control signals to compilepartial cell features from the raster scanned signals on a line-by-linebasis for each said identified cell segment;
 9. algebraically combiningthe vertically connected sample region classification signals to producesecond control signals;
 9. means for assigning a cell tag to each ofsaid identified cell segment in response to said control signals andsaid sample region classification signals; and,
 9. means for generatingcell tags;
 9. utilizing said first and second control signals to compilepartial cell features from the raster scanned signals on a line-by-linebasis for each said identified cell segment;
 10. generating cell tags;10. means for generating cell tags;
 10. means for assigning a cell tagto each of said identified cell segments in response to said controlsignals and said sample region classification signals and as a functionof the existence of a previously assigned cell tag, said previouslyassigned cell tag being delayed to re-establish its vertical connectionwith the identified cell segment; and,
 10. means for utilizing each celltag to sequentially compile complete cell features from the partial cellfeatures of each identified cell segment having the same cell tag. 10.algebraically combining the vertically connected sample regionclassification signals to produce second control signals;
 10. utilizingsaid first control signals to identify cell segments in the digitizedserial data signals;
 10. means for generating cell tags;
 10. utilizingsaid first and second control signals to compile partial cell featuresfrom the raster scanned signals on a line-by-line basis for each saididentified cell segment;
 10. means for assigning a cell tag to each ofsaid identified cell segment in response to said control signals andsaid sample region classification signals; and,
 10. means for generatingcell tags;
 10. means for utilizing said first control signals toidentify cell segments in the digitized serial data signals;
 10. Amethod of blood cell analysis comprising the steps of:
 10. utilizingeach cell tag to sequentially compile complete cell features from thepartial cell features of each identified cell segment having the samecell tag.
 10. means for utilizing said first and second control signalsto compile partial cell features from the digitized serial data signalson a line-by-line basis for each said identified cell segment; 10.assigning a cell tag to each of said identified cell segment in responseto said control signals and said sample region classification signals;and,
 11. means for utilizing said first and second control signals tocompile partial cell features from the digitized serial data signals ona line-by-line basis for each said identified cell segment;
 11. meansfor generating cell tags;
 11. means for assigning a cell tag to each ofsaid identified cell segments in response to said control signals andsaid sample region classification signals and as a function of theexistence of a previously assigned cell tag, said previously assignedcell tag being delayed to re-establish its vertical connection with theidentified cell segment; and,
 11. utilizing each cell tag tosequentially compile complete cell features from the partial cellfeatures of each identified cell segment having the same cell tag. 11.means for utilizing each cell tag to sequentially compile complete cellfeatures from the partial cell features of each identified cell segmenthaving the same cell tag.
 11. A method of blood cell analysis comprisingthe steps of:
 11. means for assigning cell tag to each of saididentified cell segments in response to said control signals and saidsample region classification signals and as a function of the existenceof a previously assigned cell tag with said previously assigned cell tagbeing delayed to re-establish its vertical connection with theidentified cell segment; and,
 11. meAns for utilizing each cell tag tosequentially compile complete cell features from the partial cellfeatures of each identified cell segment having the same cell tag. 11.generating cell tags;
 11. means for assigning a cell tag to each of saididentified cell segments in response to said control signals and saidsample region classification signals and as a function of the existenceof a previously assigned cell tag, said previously assigned cell tagbeing delayed to re-establish its vertical connection with theidentified cell segment; and,
 11. utilizing said first and secondcontrol signals to compile partial cell features from the digitizedserial data signals on a line-by-line basis for each said identifiedcell segment;
 11. utilizing said first control signals to identify cellsegments in the digitized serial data signals;
 11. assigning a cell tagto each of said identified cell segments in response to said controlsignals and said sample region classification signals and as a functionof the existence of a previously assigned cell tag, said previouslyassigned cell tag being delAyed to re-establish its vertical connectionwith the identified cell segment; and,
 12. utilizing each cell tag tosequentially compile complete cell features from the partial cellfeatures of each identified cell segment having the same cell tag. 12.generating cell tags;
 12. utilizing said first and second controlsignals to compile partial cell features from the digitized serial datasignals on a line-by-line basis for each said identified cell segment;12. assigning cell tag to each of said identified cell segments inresponse to said control signals and said sample region classificationsignals and as a function of the existence of a previously assigned celltag, said previously assigned cell tag being delayed to re-establish itsvertical connection with the identified cell segment; and,
 12. A methodof blood cell analysis comprising the steps of:
 12. means for utilizingeach cell tag to sequentially compile complete cell features from thepartial cell features of each identified cell segment having the samecell tag.
 12. means for generating cell tags;
 12. means utilizing eachcell tag for sequentially compiling complete cell features from thepartial cell features of each identified cell segment having the samecell tag.
 12. means for utilizing each cell tag to sequentially compilecomplete cell features from the partial cell features of each identifiedcell segment having the same cell tag.
 12. means for assigning a celltag to each of said identified cell segments in response to said controlsignals and said sample region classification signals and as a functionof the existence of a previously assigned cell tag, said previouslyassigned cell tag being delayed to re-establish its vertical connectionwith the identified cell segment; and,
 13. means for utilizing each celltag to sequentially compile complete cell features from the partial cellfeatures of each idenTified cell segment having the same cell tag. 13.generating cell tags;
 13. utilizing each cell tag to sequentiallycompile complete cell features from the partial cell features of eachidentified cell segment having the same cell tag.
 13. A method ofanalyzing an illuminated sample comprising the steps of:
 13. means forassigning a cell tag to each of said identified cell segments inresponse to said control signals and said sample region classificationsignals and as a function of the existence of a previously assigned celltag, said previously assigned cell tag being delayed to re-establish itsvertical connection with the identified cell segment; and,
 13. assigninga cell tag to each oF said identified cell segments in response to saidcontrol signals and said sample region classification signals and as afunction of the existence of a previously assigned cell tag, saidpreviously assigned cell tag being delayed to re-establish its verticalconnection with the identified cell segment; and,
 14. The method ofclaim 13 wherein said complete sample features are compiled by: 14.utilizing each cell tag to sequentially compile complete cell featuresfrom the partial cell features of each identified cell segment havingthe same cell tag.
 14. means for utilizing each cell tag to sequentiallycompile complete cell features from the partial cell features of eachidentified cell segment having the same cell tag.
 14. assigning a celltag to each of said identified cell segments in response to said controlsignals and said sample region classification signals and as a functionof the existence of a previously assigned cell tag, said previouslyassigned cell tag being delayed to re-establish its vertical connectionwith the identified cell segment; and
 15. A method of sample analysiscomprising the steps of:
 15. utilizing each tag to sequentially compilecomplete cell features from the partial cell features of each identifiedcell segment having the same cell tag.
 16. A method of sample analysiscomprising the steps of:
 17. The method of claim 16 wherein saidcomplete sample features are compiled by:
 18. A method of sampleanalysis comprising the steps of:
 19. A method of blood cell analysiscomprising the steps of:
 20. A method of blood cell analysis comprisingthe steps of:
 21. A method of blood cell analysis comprising the stepsof:
 22. A method of blood cell analysis comprising the steps of:
 23. Amethod of blood cell analysis comprising the steps of:
 24. A method ofblood cell analysis comprising the steps of:
 25. A method of blood cellanalysis comprising the steps of:
 26. An apparatus for analyzing anilluminated subject comprising:
 27. An apparatus for blood cell analysiscomprising:
 28. The apparatus of claim 27 wherein:
 29. An apparatus forblood cell analysis comprising:
 30. The apparatus of claim 29 wherein:31. The apparatus of claim 29 wherein:
 32. The apparatus of claim 29wherein:
 33. An apparatus for analyzing an illuminated samplecomprising:
 34. The apparatus of claim 33 wherein said means forcompiling complete sample features comprises:
 35. An apparatus forsample analysis comprising:
 36. The apparatus of claim 35 wherein saidmeans for compiling complete sample features comprises:
 37. An apparatusfor blood cell analysis compriSing:
 38. An apparatus for blood cellanalysis comprising:
 39. A method of sample analysis comprising thesteps of:
 40. An apparatus for sample analysis comprising:
 41. Anapparatus for blood cell analysis comprising:
 42. An apparatus for bloodcell analysis comprising:
 43. An apparatus for blood cell analysiscomprising:
 44. The apparatus of claim 43 wherein said algebraicallycombined signal is the sum of said first and second signals.
 45. Theapparatus of claim 43 wherein said algebraically combined sigNal is thedifference of said first and second signals.
 46. A method of blood cellanalysis comprising the steps of:
 47. The method of claim 46 whereinsaid algebraically combined signal is the sum of said first and secondsignals.
 48. The method of claim 46 wherein said algebraically combinedsignal is the sum of said first and second signals.
 49. An apparatus forblood cell analysis comprising:
 50. A method of blood cell analysiscomprising the steps of:
 51. An apparatus for blood cell analysiscomprising:
 52. An apparatus for blood cell analysis comprising:
 53. Anapparatus for blood cell analysis comprising:
 54. An apparatus for bloodcell analysis comprising:
 55. An apparatus for blood cell analysiscomprising:
 56. An apparatus for blood cell analysis comprising:
 57. Anapparatus for blood cell analysis comprising:
 58. An apparatus for bloodcell analysis comprising:
 59. An apparatus for blood cell analysiscomprising: